Cluster-Enhanced Nanopore Sensing of Ovarian Cancer Marker Peptides in Urine

作者：Thomas W. Rockett, Mohammed Almahyawi, Madhav Ghimire, Aashna Jonnalagadda, Victoria Tagliaferro, Sarah J. Seashols‐Williams, Massimo F. Bertino, Gregory A. Caputo, Joseph E. Reiner · 发表于：ACS Sensors · 年份：2024 · DOI：10.1021/acssensors.3c02207 · 被引用次数：17 · 研究领域：Nanopore and Nanochannel Transport Studies、Geophysical and Geoelectrical Methods、Model Reduction and Neural Networks

The development of novel methodologies that can detect biomarkers from cancer or other diseases is both a challenge and a need for clinical applications. This partly motivates efforts related to nanopore-based peptide sensing. Recent work has focused on the use of gold nanoparticles for selective detection of cysteine-containing peptides. Specifically, tiopronin-capped gold nanoparticles, trapped in the cis-side of a wild-type α-hemolysin nanopore, provide a suitable anchor for the attachment of cysteine-containing peptides. It was recently shown that the attachment of these peptides onto a nanoparticle yields unique current signatures that can be used to identify the peptide. In this article, we apply this technique to the detection of ovarian cancer marker peptides ranging in length from 8 to 23 amino acid residues. It is found that sequence variability complicates the detection of low-molecular-weight peptides (<10 amino acid residues), but higher-molecular-weight peptides yield complex, high-frequency current fluctuations. These fluctuations are characterized with chi-squared and autocorrelation analyses that yield significantly improved selectivity when compared to traditional open-pore analysis. We demonstrate that the technique is capable of detecting the only two cysteine-containing peptides from LRG-1, an emerging protein biomarker, that are uniquely present in the urine of ovarian cancer patients. We further demonstrate the detection of one of these LRG-1 peptides s...